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Analyzing the Flow of Knowledge with Sociometric Badges

机译:使用社会计量学徽章分析知识流

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This paper presents a collection of “best practices” for the use of “Sociometric Badges” that support automatic collection of face-to-face interaction between workers within an organization. The practices presented aim to improve data quality over legacy methods allowing insights into the processes and structures of an enterprise's de-facto communication networks. Our approach uses dynamic Social Network Analysis (dSNA) to make it easier for executives to analyze and manage communications networks. The practical applicability of the approach was evaluated by case studies conducted in three different organizations: (1) the marketing department of a medium sized bank in Germany, (2) the post-anesthesia care unit at a large US hospital, (3) teams of software developers in a Nordic European country. For the analysis, we tracked, amongst others, all personal interactions between the knowledge workers in a department or team using sociometric badges worn by each employee for the duration of the case studies. We analyzed this sociometric data as well as emails and instant messages exchanged between the employees and compared it with performance data of individuals and teams. The paper highlights 16 key lessons learnt during these studies. The first nine lessons focus on overcoming the employee's privacy concerns to set up the necessary technology infrastructure, and the final seven provide general findings for efficient management of knowledge workers based upon the results of the case studies.
机译:本文介绍了使用“社会计量徽章”的“最佳实践”集合,这些集合支持自动收集组织内员工之间的面对面互动。提出的实践旨在通过允许对企业实际通信网络的流程和结构进行洞察的传统方法来提高数据质量。我们的方法使用动态社交网络分析(dSNA),使高管更容易分析和管理通讯网络。通过在三个不同组织中进行的案例研究评估了该方法的实际适用性:(1)德国一家中型银行的营销部门;(2)美国一家大型医院的麻醉后护理部门;(3)团队欧洲北欧国家/地区的软件开发人员数量。为了进行分析,我们使用案例研究期间每位员工佩戴的社会计量学徽章,跟踪了部门或团队中知识工作者之间的所有个人互动。我们分析了这些社会统计数据以及员工之间交换的电子邮件和即时消息,并将其与个人和团队的绩效数据进行了比较。本文重点介绍了在这些研究中吸取的16个主要经验教训。前九节课着重于解决员工的隐私问题,以建立必要的技术基础架构,最后七节课提供了基于案例研究结果的有效管理知识工作者的一般发现。

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